Systems biochemistry to "deorphanize" human mitochondrial proteome.

Rensvold, Shishkova, et al. (2022) apply an integrated systems biology approach spanning proteomics, lipidomics, and metabolomics to a collection of CRISPR knockout cells targeting 116 distinct human mitochondrial proteins, revealing new mitochondrial biology and guiding orphan disease diagnosis.

An astonishing regularity in student learning rate.

Leveraging a scientific infrastructure for exploring how students learn, we have developed cognitive and statistical models of skill acquisition and used them to understand fundamental similarities and differences across learners. Our primary question was why do some students learn faster than others? Or, do they? We model data from student performance on groups of tasks that assess the same skill component and that provide follow-up instruction on student errors. Our models estimate, for both students and skills, initial correctness and learning rate, that is, the increase in correctness after each practice opportunity. We applied our models to 1.3 million observations across 27 datasets of student interactions with online practice systems in the context of elementary to college courses in math, science, and language. Despite the availability of up-front verbal instruction, like lectures and readings, students demonstrate modest initial prepractice performance, at about 65% accuracy. Despite being in the same course, students' initial performance varies substantially from about 55% correct for those in the lower half to 75% for those in the upper half. In contrast, and much to our surprise, we found students to be astonishingly similar in estimated learning rate, typically increasing by about 0.1 log odds or 2.5% in accuracy per opportunity. These findings pose a challenge for theories of learning to explain the odd combination of large variation in student initial performance and striking regularity in student learning rate.

Bacterial indole-3-lactic acid affects epithelium-macrophage crosstalk to regulate intestinal homeostasis.

Tryptophan and its derivatives perform a variety of biological functions; however, the role and specific mechanism of many tryptophan derivatives in intestinal inflammation remain largely unclear. Here, we identified that an Escherichia coli strain (Ec-TMU) isolated from the feces of tinidazole-treated individuals, and indole-3-lactic acid (ILA) in its supernatant, decreased the susceptibility of mice to dextran sulfate sodium-induced colitis. Ec-TMU and ILA contribute to the relief of colitis by inhibiting the production of epithelial CCL2/7, thereby reducing the accumulation of inflammatory macrophages in vitro and in vivo. Mechanistically, ILA downregulates glycolysis, NF-κB, and HIF signaling pathways via the aryl hydrocarbon receptor, resulting in decreased CCL2/7 production in epithelial cells. Clinical evidence suggests that the fecal ILA level is negatively correlated with the progression indicator of inflammatory bowel diseases. These results demonstrate that ILA has the potential to regulate intestinal homeostasis by modulating epithelium-macrophage interactions.

A Bayesian approach to estimate MHC-peptide binding threshold.

Major histocompatibility complex (MHC)-peptide binding is a critical step in enabling a peptide to serve as an antigen for T-cell recognition. Accurate prediction of this binding can facilitate various applications in immunotherapy. While many existing methods offer good predictive power for the binding affinity of a peptide to a specific MHC, few models attempt to infer the binding threshold that distinguishes binding sequences. These models often rely on experience-based ad hoc criteria, such as 500 or 1000nM. However, different MHCs may have different binding thresholds. As such, there is a need for an automatic, data-driven method to determine an accurate binding threshold. In this study, we proposed a Bayesian model that jointly infers core locations (binding sites), the binding affinity and the binding threshold. Our model provided the posterior distribution of the binding threshold, enabling accurate determination of an appropriate threshold for each MHC. To evaluate the performance of our method under different scenarios, we conducted simulation studies with varying dominant levels of motif distributions and proportions of random sequences. These simulation studies showed desirable estimation accuracy and robustness of our model. Additionally, when applied to real data, our results outperformed commonly used thresholds.

Quantum Hall effect based on Weyl orbits in Cd3As2.

Discovered decades ago, the quantum Hall effect remains one of the most studied phenomena in condensed matter physics and is relevant for research areas such as topological phases, strong electron correlations and quantum computing1-5. The quantized electron transport that is characteristic of the quantum Hall effect typically originates from chiral edge states-ballistic conducting channels that emerge when two-dimensional electron systems are subjected to large magnetic fields2. However, whether the quantum Hall effect can be extended to higher dimensions without simply stacking two-dimensional systems is unknown. Here we report evidence of a new type of quantum Hall effect, based on Weyl orbits in nanostructures of the three-dimensional topological semimetal Cd3As2. The Weyl orbits consist of Fermi arcs (open arc-like surface states) on opposite surfaces of the sample connected by one-dimensional chiral Landau levels along the magnetic field through the bulk6,7. This transport through the bulk results in an additional contribution (compared to stacked two-dimensional systems and which depends on the sample thickness) to the quantum phase of the Weyl orbit. Consequently, chiral states can emerge even in the bulk. To measure these quantum phase shifts and search for the associated chiral modes in the bulk, we conduct transport experiments using wedge-shaped Cd3As2 nanostructures with variable thickness. We find that the quantum Hall transport is strongly modulated by the sample thickness. The dependence of the Landau levels on the magnitude and direction of the magnetic field and on the sample thickness agrees with theoretical predictions based on the modified Lifshitz-Onsager relation for the Weyl orbits. Nanostructures of topological semimetals thus provide a way of exploring quantum Hall physics in three-dimensional materials with enhanced tunability.

Involvement of CgHSFB1 in the regulation of self-incompatibility in 'Shatian' pummelo.

As self-incompatibility is a major issue in pummelo breeding and production, its mechanism in citrus was analyzed to improve breeding efficiency and reduce production costs. Rutaceae belongs to S-RNase type of gametophytic self-incompatibility. While the function of S-RNase/SLF and the mechanism of self-incompatibility have been studied extensively, the transcriptional regulation of S-RNase has been less studied. We performed transcriptome sequencing with the styles of 'Shatian' pummelo on the day of anthesis and 1-5 days before anthesis, and found that the transcript level of S-RNase gradually decreased with flower development. By analyzing differentially expressed genes and correlation with the expression trend of S-RNase, we identified a candidate gene, CgHSFB1, and utilized biochemical experiments such as yeast one-hybrid assay, electrophoretic mobility shift assay and dual-luciferase assay, as well as transient transformation of citrus calli and Citrus microcarpa and demonstrated that CgHSFB1 could directly bind to the S1-RNase promoter and repress the expression of S1-RNase, which is involved in the pummelo self-incompatibility response. In contrast, CgHSFB1 did not bind to the promoter of S2-RNase, and there was specificity in the regulation of S-RNase.

Vitamin C Drives Reentrant Actin Phase Transition: Biphasic Exocytosis Regulation Revealed by Single-Vesicle Electrochemistry.

Unveiling molecular mechanisms that dominate protein phase dynamics has been a pressing need for deciphering the intricate intracellular modulation machinery. While ions and biomacromolecules have been widely recognized for modulating protein phase separations, effects of small molecules that essentially constitute the cytosolic chemical atmosphere on the protein phase behaviors are rarely understood. Herein, we report that vitamin C (VC), a key small molecule for maintaining a reductive intracellular atmosphere, drives reentrant phase transitions of myosin II/F-actin (actomyosin) cytoskeletons. The actomyosin bundle condensates dissemble in the low-VC regime and assemble in the high-VC regime in vitro or inside neuronal cells, through a concurrent myosin II protein aggregation-dissociation process with monotonic VC concentration increase. Based on this finding, we employ in situ single-cell and single-vesicle electrochemistry to demonstrate the quantitative modulation of catecholamine transmitter vesicle exocytosis by intracellular VC atmosphere, i.e., exocytotic release amount increases in the low-VC regime and decreases in the high-VC regime. Furthermore, we show how VC regulates cytomembrane-vesicle fusion pore dynamics through counteractive or synergistic effects of actomyosin phase transitions and the intracellular free calcium level on membrane tensions. Our work uncovers the small molecule-based reversive protein phase regulatory mechanism, paving a new way to chemical neuromodulation and therapeutic repertoire expansion.

Tuning the Flat Band in Bi2O2Se by Pressure to Induce Superconductivity.

The discovery of superconductivity in twisted bilayer graphene has reignited enthusiasm in the field of flat-band superconductivity. However, important challenges remain, such as constructing a flat-band structure and inducing a superconducting state in materials. Here, we successfully achieved superconductivity in Bi2O2Se by pressure-tuning the flat-band electronic structure. Experimental measurements combined with theoretical calculations reveal that the occurrence of pressure-induced superconductivity at 30 GPa is associated with a flat-band electronic structure near the Fermi level. Moreover, in Bi2O2Se, a van Hove singularity is observed at the Fermi level alongside pronounced Fermi surface nesting. These remarkable features play a crucial role in promoting strong electron-phonon interactions, thus potentially enhancing the superconducting properties of the material. These findings demonstrate that pressure offers a potential experimental strategy for precisely tuning the flat band and achieving superconductivity.

Enzymatic Galvanic Redox Potentiometry for In Vivo Biosensing.

Redox potentiometry has emerged as a new platform for in vivo sensing, with improved neuronal compatibility and strong tolerance against sensitivity variation caused by protein fouling. Although enzymes show great possibilities in the fabrication of selective redox potentiometry, the fabrication of an enzyme electrode to output open-circuit voltage (EOC) with fast response remains challenging. Herein, we report a concept of novel enzymatic galvanic redox potentiometry (GRP) with improved time response coupling the merits of the high selectivity of enzyme electrodes with the excellent biocompatibility and reliability of GRP sensors. With a glucose biosensor as an illustration, we use flavin adenine dinucleotide-dependent glucose dehydrogenase as the recognition element and carbon black as the potential relay station to improve the response time. We find that the enzymatic GRP biosensor rapidly responds to glucose with a good linear relationship between EOC and the logarithm of glucose concentration within a range from 100 µM to 2.65 mM. The GRP biosensor shows high selectivity over O2 and coexisting neurochemicals, good reversibility, and sensitivity and can in vivo monitor glucose dynamics in rat brain. We believe that this study will pave a new platform for the in vivo potentiometric biosensing of chemical events with high reliability.

Rationally Construction of Mn-Doped RuO2 Nanofibers for High-Activity and Stable Alkaline Ampere-Level Current Density Overall Water Splitting.

Nowadays, highly active and stable alkaline bifunctional electrocatalysts toward water electrolysis that can work at high current density (≥1000 mA cm-2) are urgently needed. Herein, Mn-doped RuO2 (MnxRu1-xO2) nanofibers (NFs) are constructed to achieve this object, presenting wonderful hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) performances with the overpotentials of only 269 and 461 mV at 1 A cm-2 in 1 m KOH solution, and remarkably stability under industrial demand with 1 A cm-2, significantly better than the benchmark Pt/C and commercial RuO2 electrocatalysts, respectively. More importantly, the assembled Mn0.05Ru0.95O2 NFs||Mn0.05Ru0.95O2 NFs electrolyzer toward overall water splitting reaches the current density of 10 mA cm-2 with a cell voltage of 1.52 V and also delivers an outstanding stability over 150 h of continuous operation, far surpassing commercial Pt/C||commercial RuO2, RuO2 NFs||RuO2 NFs and most previously reported exceptional electrolyzers. Theoretical calculations indicate that Mn-doping into RuO2 can significantly optimize the electronic structure and weaken the strength of O─H bond to achieve the near-zero hydrogen adsorption free energy (ΔGH*) value for HER, and can also effectively weaken the adsorption strength of intermediate O* at the relevant sites, achieving the higher OER catalytic activity, since the overlapping center of p-d orbitals is closer to the Fermi level.

Fusobacterium periodonticum BCT protein targeting glucose metabolism to promote the epithelial-mesenchymal transition of esophageal cancer cells by lactic acid.

BACKGROUND: The cancer microbiota was considered the main risk factor for cancer progression. We had proved that Fusobacterium periodonticum (F.p) was higher abundance in Esophageal cancer(EC)tissues. Bioinformation analysis found that BCT was a key virulence protein of F.p. However, little is known about the role and mechanism of BCT in EC. This study aimed to recognize the key virulence protein of F.p and explore the mechanism of BCT in promoting EC. METHODS: We constructed a eukaryotic expression vector and purified the recombinant protein BCT. CCK8 used to analyzed the activity of EC after treated by different concentration of BCT. UPLC-MS/MS and ELISA used to detect the metabonomics and metabolites. The ability of migration and invasion was completed by transwell assay. RT-QPCR, WB used to analyze the expression of relevant genes. RESULTS: Our data showed that BCT was higher expression in EC tumor tissues (p < 0.05) and BCT in 20 µg/mL promoted the survival, invasion and migration of EC cells (EC109) (p < 0.05). Meanwhile, UPLC-MS/MS results suggested that BCT resulted in an augmentation of hypotaurine metabolism, arachidonic acid metabolism, glycolysis/gluconeogenesis, tryptophan metabolism, citrate cycle activity in EC109. The metabolic changes resulted in decreasing in glucose and pyruvate levels but increase in lactate dehydrogenase (LDH) activity and lactic acid (LA) as well as the expression of glucose transporter 1, Hexokinase 2, LDH which regulated the glycolysis were all changed (p < 0.05). The BCT treatment upregulated the expression of TLR4, Akt, HIF-1α (p < 0.05) which regulated the production of LA. Furthermore, LA stimulation promoted the expression of GPR81, Wnt, and ß-catenin (p < 0.05), thereby inducing EMT and metastasis in EC109 cells. CONCLUSION: Altogether, these findings identified that impact of BCT in regulation of glycolysis in EC109 and its involves the TLR4/Akt/HIF-1α pathway. Meanwhile, glycolysis increasing the release of LA and promote the EMT of EC109 by GPR81/Wnt/ß-catenin signaling pathway. In summary, our findings underscore the potential of targeting BCT as an innovative strategy to mitigate the development of EC.

Temperature-dependent electroluminescence of red high-In-content MQWs of dual-wavelength micro-LED.

Temperature-dependent electroluminescence (TDEL) measurements have been employed to investigate the carrier transport and recombination processes of InGaN red micro-LED based on dual-wavelength InGaN/GaN MQWs structure. EL peak energy and carrier transport of the red micro-LED both show temperature dependence, due to temperature-induced changes in defect activation. In addition, the current density at which the blue peak of the low-In-content appears in the EL spectrum varies with temperature. As the temperature increases, the blue peak of the low In component tends to appear at higher current densities, which may be attributed to the increase in thermally activated defects hindering the injection of holes into the low-In-content MQWs further away from p-GaN. Furthermore, the IQEs of the high-In-content MQWs are estimated from the TDEL method and then reveal the temperature-dependent efficiency droop. The IQE decreases as temperature increases, particularly above 50 K, where it drops sharply due to temperature-dependent nonradiative recombination. And the two different variation trends in IQE of MQWs with high and low In content reveal a competitive mechanism in carrier distribution, implying that more escaping holes from high-In-content MQWs will further reduce red emission efficiency but enhance carrier injection and blue emission in low-In-content MQWs.

Selective Detection of Dynamics-Complete Set of Correlations via Quantum Channels.

Correlations of fluctuations are essential to understanding many-body systems and key information for advancing quantum technologies. To fully describe the dynamics of a physical system, all time-ordered correlations (TOCs), i.e., the dynamics-complete set of correlations are needed. The current measurement techniques can only access a limited set of TOCs, and there has been no systematic and feasible solution for extracting the dynamic-complete set of correlations hitherto. Here we propose a platform-universal protocol to selectively detect arbitrary types of TOCs via quantum channels. In our method, the quantum channels are synthesized with various controls, and engineer the evolution of a sensor-target system along a specific path that corresponds to a desired correlation. Using nuclear magnetic resonance, we experimentally demonstrate this protocol by detecting a specific type of fourth-order TOC that has never been accessed previously. We also show that the knowledge of the TOCs can be used to significantly improve the precision of quantum optimal control. Our method provides a new toolbox for characterizing the quantum many-body states and quantum noise, and hence for advancing the fields of quantum sensing and quantum computing.

Multichannel Multijunction Droplet Microfluidic Device to Synthesize Hydrogel Microcapsules with Different Core-Shell Structures and Adjustable Core Positions.

Core-shell hydrogel microcapsules have sparked great interest due to their unique characteristics and prospective applications in the medical, pharmaceutical, and cosmetic fields. However, complex synthetic procedures and expensive costs have limited their practical application. Herein, we designed and prepared several multichannel and multijunctional droplet microfluidic devices based on soft lithography for the effective synthesis of core-shell hydrogel microcapsules for different purposes. Additionally, two different cross-linking processes (ultraviolet (UV) exposure and interfacial polymerization) were used to synthesize different types of core-shell structured hydrogel microcapsules. Hydrogel microcapsules with gelatin methacryloyl (GelMA) as the core and polyacrylamide (PAM) as the thin shell were synthesized using UV cross-linking. Using an interfacial polymerization process, another core-shell structured microcapsule with GelMA as the core and Ca2+ cross-linked alginate with polyethylenimine (PEI) as the shell was constructed, and the core diameter and total droplet diameter were flexibly controlled by carving. Noteworthy, these hydrogel microcapsules exhibit stimuli-responsiveness and controlled release ability. Overall, a novel technique was developed to successfully synthesize various hydrogel microcapsules with core-shell microstructures. The hydrogel microcapsules possess a multilayered structure that facilitates the coassembly of cells and drugs, as well as the layered assembly of multiple drugs, to develop synergistic therapeutic regimens. These adaptable and controllable hydrogel microdroplets shall held great promise for multicell or multidrug administration as well as for high-throughput drug screening.

Mad2 promotes Cyclin B2 recruitment to the kinetochore for guiding accurate mitotic checkpoint.

Accurate mitotic progression relies on the dynamic phosphorylation of multiple substrates by key mitotic kinases. Cyclin-dependent kinase 1 is a master kinase that coordinates mitotic progression and requires its regulatory subunit Cyclin B to ensure full kinase activity and substrate specificity. The function of Cyclin B2, which is a closely related family member of Cyclin B1, remains largely elusive. Here, we show that Mad2 promotes the kinetochore localization of Cyclin B2 and that their interaction at the kinetochores guides accurate chromosome segregation. Our biochemical analyses have characterized the Mad2-Cyclin B2 interaction and delineated a novel Mad2-interacting motif (MIM) on Cyclin B2. The functional importance of the Cyclin B2-Mad2 interaction was demonstrated by real-time imaging in which MIM-deficient mutant Cyclin B2 failed to rescue the chromosomal segregation defects. Taken together, we have delineated a previously undefined function of Cyclin B2 at the kinetochore and have established, in human cells, a mechanism of action by which Mad2 contributes to the spindle checkpoint.

A computational approach to estimate postmortem interval using postmortem computed tomography of multiple tissues based on animal experiments.

The estimation of postmortem interval (PMI) is a complex and challenging problem in forensic medicine. In recent years, many studies have begun to use machine learning methods to estimate PMI. However, research combining postmortem computed tomography (PMCT) with machine learning models for PMI estimation is still in early stages. This study aims to establish a multi-tissue machine learning model for PMI estimation using PMCT data from various tissues. We collected PMCT data of seven tissues, including brain, eyeballs, myocardium, liver, kidneys, erector spinae, and quadriceps femoris from 10 rabbits after death. CT images were taken every 12 h until 192 h after death, and HU values were extracted from the CT images of each tissue as a dataset. Support vector machine, random forest, and K-nearest neighbors were performed to establish PMI estimation models, and after adjusting the parameters of each model, they were used as first-level classification to build a stacking model to further improve the PMI estimation accuracy. The accuracy and generalized area under the receiver operating characteristic curve of the multi-tissue stacking model were able to reach 93% and 0.96, respectively. Results indicated that PMCT detection could be used to obtain postmortem change of different tissue densities, and the stacking model demonstrated strong predictive and generalization abilities. This approach provides new research methods and ideas for the study of PMI estimation.

Development and multicentre validation of the FLEX score: personalised preoperative surgical risk prediction using attention-based ICD-10 and Current Procedural Terminology set embeddings.

BACKGROUND: Preoperative knowledge of surgical risks can improve perioperative care and patient outcomes. However, assessments requiring clinician examination of patients or manual chart review can be too burdensome for routine use. METHODS: We conducted a multicentre retrospective study of 243 479 adult noncardiac surgical patients at four hospitals within the Mass General Brigham (MGB) system in the USA. We developed a machine learning method using routinely collected coding and patient characteristics data from the electronic health record which predicts 30-day mortality, 30-day readmission, discharge to long-term care, and hospital length of stay. RESULTS: Our method, the Flexible Surgical Set Embedding (FLEX) score, achieved state-of-the-art performance to identify comorbidities that significantly contribute to the risk of each adverse outcome. The contributions of comorbidities are weighted based on patient-specific context, yielding personalised risk predictions. Understanding the significant drivers of risk of adverse outcomes for each patient can inform clinicians of potential targets for intervention. CONCLUSIONS: FLEX utilises information from a wider range of medical diagnostic and procedural codes than previously possible and can adapt to different coding practices to accurately predict adverse postoperative outcomes.

Real-world effectiveness and safety of evolocumab in very high-risk atherosclerotic cardiovascular disease patients with acute ischemic stroke.

BACKGROUND: We investigated evolocumab's real-world effectiveness and safety on a background of statin therapy in the acute phase of ischemic stroke (IS) patients with a very high-risk of atherosclerotic cardiovascular disease (ASCVD). METHODS: A real-world, single-center, retrospective study was conducted in the neurology department at Tianjin Huanhu Hospital in China. Patients were divided into two groups: evolocumab treatment (140 mg every two weeks) or the standard of care (SOC) group. The primary efficacy outcome of the study was the achievement of a targeted lipid control rate and the incidence of major adverse cardiovascular events (MACE) by the end of the follow-up. MACE was defined as a composite of various cardiovascular events, cerebrovascular events such as stroke or TIA, and event-related deaths. Propensity score matching (PSM) analysis was utilized to account for confounding factors between groups. Survival analyses were performed using the Kaplan-Meier method and COX regression modeling. RESULTS: 1080 AIS patients with very high-risk ASCVD were recruited. After PSM, there were 528 individuals, with 206 in the evolocumab group and 322 in the SOC group. At 12 months of follow-up, the proportion of LDL-C < 1.4mmol/L and ≥ 50% reduction was 44.91% in the evolocumab group, compared with only 3.12% of SOC-treated patients (p < 0.01). The median follow-up time for clinical events was 15 months. The evolocumab group was associated with a lower risk of cerebrovascular events compared to the SOC group (HR, 0.45; 95% CI, 0.23-0.89; p = 0.02). CONCLUSIONS: This real-world study suggested that evolocumab on a background of statin reduced the LDL-C levels significantly and lowered the incidence of recurrent cerebrovascular events in the very high-risk ASCVD patients with AIS in China.

UBE2T resolves transcription-replication conflicts and protects common fragile sites in primordial germ cells.

The proper development of primordial germ cells (PGCs) is an essential prerequisite for gametogenesis and mammalian fertility. The Fanconi anemia (FA) pathway functions in maintaining the development of PGCs. FANCT/UBE2T serves as an E2 ubiquitin-conjugating enzyme that ubiquitylates the FANCD2-FANCI complex to activate the FA pathway, but its role in the development of PGCs is not clear. In this study, we found that Ube2t knockout mice showed defects in PGC proliferation, leading to severe loss of germ cells after birth. Deletion of UBE2T exacerbated DNA damage and triggered the activation of the p53 pathway. We further demonstrated that UBE2T counteracted transcription-replication conflicts by resolving R-loops and stabilizing replication forks, and also protected common fragile sites by resolving R-loops in large genes and promoting mitotic DNA synthesis to maintain the genome stability of PGCs. Overall, these results provide new insights into the function and regulatory mechanisms of the FA pathway ensuring normal development of PGCs.

COVID-19 in patients with myasthenia gravis: a single-center retrospective study in China.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has been a great concern since 2019. Patients with myasthenia gravis (MG) may be at higher risk of COVID-19 and a more severe disease course. We examined the associations between COVID-19 and MG. METHODS: This single-center retrospective cohort study involved 134 patients who were diagnosed with MG from June 2020 to November 2022 and followed up until April 2023. They were divided into a COVID-19 group and non-COVID-19 group. Logistic regression analysis was used to detect factors potentially associating COVID-19 with MG. RESULTS: Of the 134 patients with MG, 108 (80.6%) had COVID-19. A higher number of comorbidities was significantly associated with an increased risk of COVID-19 (p = 0.040). A total of 103 patients (95.4%) had mild/moderate COVID-19 symptoms, and 4 patients (3.7%) were severe/critical symptoms (including 2 deaths). Higher age (p = 0.036), use of rituximab (p = 0.037), tumors other than thymoma (p = 0.031), Hashimoto's thyroiditis (p = 0.011), more comorbidities (p = 0.002), and a higher baseline MG activities of daily living (MG-ADL) score (p = 0.006) were risk factors for severe COVID-19 symptoms. The MG-ADL score increased by ≥ 2 points in 16 (15.7%) patients. Dry cough and/or expectoration (p = 0.011), use of oral corticosteroids (p = 0.033), and use of more than one kind of immunosuppressant (p = 0.017) were associated with the increase of the post-COVID-19 MG-ADL score. CONCLUSION: Most patients with MG have a mild course of COVID-19. However, patients with older age, many comorbidities, a high MG-ADL score, and use of a variety of immunosuppressants during COVID-19 may be more prone to severe symptoms.